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The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution

Pharmacokinetic–pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for i...

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Autores principales: Witzany, Christopher, Rolff, Jens, Regoes, Roland R., Igler, Claudia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Microbiology Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10433423/
https://www.ncbi.nlm.nih.gov/pubmed/37522891
http://dx.doi.org/10.1099/mic.0.001368
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author Witzany, Christopher
Rolff, Jens
Regoes, Roland R.
Igler, Claudia
author_facet Witzany, Christopher
Rolff, Jens
Regoes, Roland R.
Igler, Claudia
author_sort Witzany, Christopher
collection PubMed
description Pharmacokinetic–pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.
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spelling pubmed-104334232023-08-18 The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution Witzany, Christopher Rolff, Jens Regoes, Roland R. Igler, Claudia Microbiology (Reading) Reviews Pharmacokinetic–pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms. Microbiology Society 2023-07-31 /pmc/articles/PMC10433423/ /pubmed/37522891 http://dx.doi.org/10.1099/mic.0.001368 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
spellingShingle Reviews
Witzany, Christopher
Rolff, Jens
Regoes, Roland R.
Igler, Claudia
The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
title The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
title_full The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
title_fullStr The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
title_full_unstemmed The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
title_short The pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
title_sort pharmacokinetic–pharmacodynamic modelling framework as a tool to predict drug resistance evolution
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10433423/
https://www.ncbi.nlm.nih.gov/pubmed/37522891
http://dx.doi.org/10.1099/mic.0.001368
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